Retirement score calculator

ABSTRACT

The present invention concerns a system for optimizing employee retirement contributions comprising an optimization computer having one or more processors configured by code executing therein to access data from one or more retirement plan participants and derive, based on the accessed data, a hierarchy of proposals to maximize one or more features of the retirement account and to transmit such a derived hierarchy, and using a remote device configured to receive the hierarchy of retirement proposals and to generate in response to the transmission, a plurality of graphical elements, each graphical element corresponding to a particular strategy.

CROSS REFERENCE TO RELATED APPLICATION

This is a continuation of U.S. patent application Ser. No. 15/179,280,filed Jun. 10, 2016, which claims the benefit of U.S. patent applicationSer. No. 62/276,956, filed Jan. 10, 2016, which are hereby incorporatedby reference in their entireties.

FIELD OF THE INVENTION

The present invention relates generally to a computer-based method andsystem for calculating employee retirement scores and generatingimplementable action plans to maximize retirement benefits in responsethereto.

BACKGROUND OF THE INVENTION

There are various retirement plans in the US such as the 401(k) plan,403(b) plan, 457 plan, Thrift Savings Plan etc. that allow an employeeto elect to have the employer contribute a portion of the employee'scash wages to the plan on a pre-tax basis. These elective deferrals arenot subject to income tax withholding at the time of deferral and theyare not reflected as taxable income on the income tax return. Forexample, an employee can elect to contribute 10% of the compensationfrom every paycheck he/she receives to his/her 401(k) account on apre-tax basis.

Another key benefit of some of these retirement plans is the matchingcontribution provided by most employers. For example, as long as theemployee makes a contribution, the employer may make a matchingcontribution up to a certain percentage. As an example, the employergives a matching contribution of $1 for each dollar the employeecontributes for up to 6% of compensation.

There is a limit to the maximum amount of money that can be contributedby an employee for any given year. This contribution limit usuallyvaries by year depending on inflation and is set by the IRS. Forexample, under a 401(k) plan for the year 2015, an employee cancontribute up to $18,000 in pre-tax money. During the year, if theemployee is aged 50 or above, then that employee is eligible tocontribute an additional $6000 in pre-tax money as catch-upcontribution. Additionally, the total employee and employercontributions are limited to the lesser of an employee's compensation or$53,000 for 2015.

Although retirement plans such as 401(k) plans are extremely popular,employees are often not aware of the maximum amount they can contributefor the year, thereby missing out on availing maximum tax savings forthe year. Additionally, employees are often not aware that they areleaving free money on the table. This happens when an employee do notcontribute at all or do not contribute enough to get the maximummatching contribution from the employer, thus missing out on the freemoney provided by the employer. Another interesting and often overlookedcase is even if an employee contributes up to the maximum contributionlimit for the year and gets matching contribution from the employer, theemployee may not be aware that he or she is still not getting the“maximum” matching contribution from the employer and leaving free moneyon the table. This occurs when the employee contributes too much moneyinitially during the year and reaches the employee contribution limitearly in the year. Since the employee is not permitted to contribute tothe plan once the contribution limit for the year has been reachedbefore the end of the year, for every subsequent paycheck thereafter theemployee is not able to make a contribution, the employee misses out onthe corresponding matching contribution from the employer, thereby notgetting the maximum “matching” contribution from the employer.

Employees generally rely on online or printed account statementsprovided by their employers or plan administrators to get informationabout their retirement accounts. These statements typically provideinformation such as how much money they have contributed, how much moneythe employer has contributed, which financial instruments the money isinvested in, how the investments are performing etc. These statements donot by themselves provide employees with direct information on whetherthey are maximizing their tax savings or maximizing their employermatching contributions for the year. Financial Engines article publishedin May 2015 estimates that employees are passing up approximately $24billion annually in employer matching contributions by not saving enoughto receive their full employer 401(k) match.

Therefore, what is needed is a system and method that automaticallydetermines the optimal retirement savings strategy based on the uniquecombination of factors present so as to not leave free money on thetable. Furthermore, what is needed is a system and method that, withoutuser input, quantifies the level of an employee's contribution as wellas the matching contribution that can be obtained from the employer soas to assist in maximizing the employee's retirement savings.Additionally, what is needed is a system and method that generates andtransmits actionable recommendations to the employee, such actionablerecommendations providing the employee with discrete options relating tochanges in allocations that will obtain optimal retirement plan outcomesand to maximize tax savings, including obtaining the maximumcontribution match from the employer.

SUMMARY OF THE INVENTION

The present invention discloses a computer-based method and system forcalculating employee retirement scores and devising recommendations formaximizing retirement benefits. Accordingly, building awareness andhelping employees by providing meaningful information and insights in aneasy to understand form, scores that quantify the level of their owncontribution (relative to the maximum allowable under law), the level ofmatching contribution expected to be received from the employer(relative to the maximum matching contribution that can be obtained fromthe employer for the year), as well as overall scores andrecommendations on how to improve scores and maximize retirementbenefits are embodied in the present invention. For example, the presentinvention is directed, in part, to calculating the following metrics foruse in implementing the procedures and work flows described herein.

Employee Contribution Score (ECS)—a metric that quantifies how theemployee is doing in terms of his own contribution relative to themaximum allowable under law. This will help determine whether theemployee is contributing the maximum allowable for a particular yearthereby availing full advantage of the tax benefit offered by thegovernment.

Employer Match Score (EMS)—a metric that quantifies the level ofmatching contribution provided the employer. This will help indicatewhether the employee is availing the maximum matching contribution fromthe employer or whether the employee is leaving any free money on thetable.

Composite Scores (CS)—a metric that provides the arithmetic averageand/or weighted averages of the two scores above that represent theComposite/Combined/Overall Score for the employee. This can be thoughtof as something similar to a credit score provided by the credit ratingagencies

In an exemplary embodiment under the invention, the scores range from0-100. But the scores can be represented in many different numericranges or many different modes of ranges viz. as letter grades such asA+, A, A−, B+, B, B− etc., descriptions such as High/Medium/Low etc.,descriptions such as Excellent/Good/Poor etc., descriptions or colorssuch as Red/Amber/Green etc.

According to the present invention, recommendations on how to improvethe scores are also disclosed. In this sense, the present invention notonly provides scores that are descriptive of the current situation of anemployee but also prescriptive in terms of how to improve their currentsituation.

In one particular and non-limiting embodiment of the system and methodsdescribed, a properly configured computer executing code thereinimplements the steps of providing a contribution optimizationapplication to a retirement plan participant for installation on awireless computing device.

A retirement optimization computer is configured to receive inputproviding at least participant data, a contribution limit for theparticipant that specifies a total amount the participant may contributeto a tax-savings retirement account, a current contribution amount thatspecifies the total amount that the participant has contributed to aretirement account for the current year, a matching limit for theparticipant that specifies the maximum amount that the participant'semployer will match a contribution to the retirement account of theparticipant for the current year and a current matching amount thatspecifies the matching amount that the employer has already contributedto the retirement account of the participant for the current year. Thecomputer is further configured by code to implement a step of generatingat least one contribution maximization value corresponding to thedifferential between the maximum employee matching funds and the amountof funds presently contributed to the retirement account by the employerand at least one tax savings maximization value being derived from atleast a comparison of total amount permitted in a tax-savings retirementaccount and the current amount contributed to the retirement account bythe employee.

Using this information, at least one contribution strategy is devised bythe processor to achieve a participant goal, wherein the participantgoal includes at least one of (i) minimizing the contributionmaximization value, (ii) minimizing the tax savings maximization value,or (iii) balancing (i) and (ii) so as to achieve the minimal possiblevalue for both (i) and (ii), wherein the computing device is furtherconfigured to rank the devised strategies based on the participant data.The computer is further configured to transmit the contribution strategyto the wireless device over the Internet using a wireless communicationchannel.

The wireless or remote device is configured to generate, on a displayconnected thereto, a graphical representation that visually depicts (i)each of the contribution strategies, (ii) a graphical indicatoridentifying the rank of each strategy relative to one another. Thewireless device is further configured to associate with the wirelessdevice, a resource link associated with each contribution strategy,selection of the link causing the wireless device to send one or moreinstructions to the computing device to implement the selectedcontribution strategy.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other features, aspects, and advantages of the presentinvention will become more fully understood from the following detaileddescription, taken in conjunction with the accompanying drawings/figuresin which:

FIG. 1A is a block diagram depicting a computer system according to thepresent invention.

FIG. 1B is a block diagram depicting a computer system according to afurther embodiment of the present invention.

FIG. 2 is a table illustrating input data supplied by a user for gettingscores and recommendations according to an exemplary embodiment underthe invention.

FIG. 3A is a table depicting process flow for calculating the scores andproviding recommendations according to a particular embodiment.

FIG. 3B is a table depicting process flow for implementing thecontribution strategy in accordance with one or more embodiments.

FIG. 4 is an exemplary table illustrating IRS rules related tocontribution limits and annual compensation limits for various years, asstored in the computer-system database.

FIG. 5 is a table illustrating numeric scores and the correspondingletter grade, High/Medium/Low score, and Red/Amber/Green score mappings,as stored in the computer-system database according to an embodimentunder the invention.

FIG. 6 is a table showing the company name, type of retirement plan,employee contribution rate, and the corresponding employer match rateand employer match limit according to an exemplary embodiment under theinvention.

DETAILED DESCRIPTION OF THE INVENTION

By way of overview and introduction, the method and system described aredirected to, in one embodiment, determining an Employee ContributionScore (ECS), Employer Match Score (EMS), and Combined Scores (CS) and toprovide actionable recommendations on how to improve the scores byoptimizing the employee's contribution and employer's matchingcontribution for retirement plans such as the 401(k) retirement plan.

For ease of explanation and discussion, the following detaileddescription addresses the system and method in terms of evaluating atraditional 401(k) plan. However, those possessing an ordinary level ofskill in the requisite art will appreciate that the systems and methodsdescribed are in no way limited to traditional 401(k) plan and can beapplied to other retirement plans including, but not limited to, SafeHarbor 401(k) plans, SIMPLE 401(k) plans, 403(b) plans, 457 plans,Thrift Savings plans and any other similar type of retirement plans.

It is seen that retirement plans such as 401(k) plans where employeesmake pre-tax contributions from their salary and employers providematching contributions have become extremely prevalent these days.Although popular, it has been found that employees do not take maximumadvantage of the benefits offered by these plans. Sometimes they do notcontribute enough to avail maximum tax savings allowed under law orreceive maximum matching contributions from the employer. Sometimes theycontribute too much and reach the contribution limit before the end ofthe year resulting in that they miss out on getting the maximum matchingcontributions from the employer. Various embodiments of computer-basedmethods and systems of the present invention are described below.Numerous specific details are set forth to provide a thoroughunderstanding of the overall structure, function, and use of theembodiments.

With reference to one or more embodiments, and as detailed in FIG. 1A, aproperly configured computer system 130 is configured to implement aseries of instructions, to effectuate a contribution optimizationapplication for use in evaluating contribution data and generatingcontribution strategies in response to the evaluated data.

Once the strategies have been generated, they are sent to a remote ormobile platform 190 via a communication channel over a network 110. Thegenerated strategies are displayed to a user for selection.

As shown in more detail with respect to FIG. 1B, upon selection by auser, the strategies are effectuated by directly accessing one or moreaccount servers 135, and altering one or more variables associated withthe participant, such alterations implemented to effectuate thestrategy.

In one embodiment of the system described, a computer or processorsystem 130, configured by one or more modules executing therein,accesses a collection of user data, tax data and employer data from oneor more data stores and calculates scores such as Employee ContributionScore (ECS), Employer Matching Score (EMS) and Composite Scores (CS)that quantify the level of contribution made by an employee to aretirement plan, the level of matching contribution provided by theemployer, and overall optimization of tax strategies. Additionally, uponscoring the user on optimization effectiveness, the processor is furtherconfigured to transmit to the user an actionable improvement plan thatprovides the user with one or more options on improving the one or morecalculated scores.

Turning to FIG. 1A, a block diagram is provided detailing theinterconnections of and between the computer-based system 130 inaccordance with one embodiment of the present invention. Thecomputer-based system 130 (sometimes referred to herein simply as“computer system” or “system”) may comprise of one or more networked,electronic computer devices such as servers, personal computers,workstations, mainframes, laptops, handheld and/or mobile computingdevices. As shown in FIG. 1A, the computer system may comprise of one ormore processor circuits 140, one or more memory units 150, and one ormore databases 170. For convenience, only one processor circuit(referred to hereinafter simply as “processor”) 140, one memory unit150, and one database 170 are shown in FIG. 1A.

In a non-limiting example, the computer system 130 and remote computer190 are commercially available or custom built computers equipped withone or more processors, graphical processing units, field programmablegate arrays, RAM and ROM memory, network interface adaptors and one ormore input or output devices. In a further embodiment, the computersystem 130 or remote computer 190 is a computer server or collection ofcomputer servers, each server configured to store, access, process,distribute or transmit data between one another and other computers ordevices accessible or connectable therewith. In still a furtherembodiment, computer system 130 or remote computer 190 is a hostedserver, virtual machine, or other collection of software modules orprograms that are interrelated and hosted in a remote accessible storagedevice (e.g. cloud storage and hosting implementation) that allows fordynamically allocated additional processors, hardware or other resourceson an “as-need” or elastic need basis. In a further embodiment, theprocessor is configured to implement elastic load balancing algorithmsto harness remote computing capacity or functionality to enable thesystem to handle computationally or otherwise resource intensive actionsand procedures.

In a particular arrangement, the computer system 130 or remote computer190 is a desktop or workstation computer using a commercially availableoperating system, e.g. Windows®, OSX®, UNIX or Linux basedimplementation. In a further configuration, the computer system 130 orremote computer 190 is a portable computing device such as an AppleIPad/IPhone® or Android® device or other commercially available mobileelectronic device configured to have access to or implement remotehardware as necessary to carry out the functions described. In otherembodiments, the computer system 130 or remote computer 190 includescustom or non-standard hardware configurations. For instance, thecomputer system 130 or remote computer 190 is a one or moremicro-computer(s) operating alone or in concert within a collection ofsuch devices, network(s), or array of other micro-computing elements,computer-on-chip(s), prototyping devices, “hobby” computing elements,home entertainment consoles and/or other hardware.

The memory 150 may store a number of software modules, such as the scorecalculation and recommendation engine 160 shown in FIG. 1 . The module160 may comprise software code that is executed by the processor 140,the execution of which causes the processor 140 to perform variousactions dictated by the software code of the various modules, asexplained further below. The processor 140 may have one or multiplecores. The memory 150 may comprise primary computer memory, such as aread only memory (ROM) and/or a random access memory (e.g., a RAM). Thememory could also comprise secondary computer memory, such as magneticor optical disk drives or flash memory, for example.

The database 170 may be implemented as computer databases, files,directories, or any other system suitable for storing data for use bycomputers. The database 170 may be embodied as solid-state memory (e.g.,ROM), hard disk drive systems, RAID, disk arrays, storage area networks(SANs), network attached storage (NAS) and/or any other suitable systemfor storing computer data. In addition, the database 170 may comprisecaches, including database caches and/or web caches.

Embodiments of the computer system may also be implemented in cloudcomputing environments. In this embodiment, “cloud computing” may bedefined as a model for enabling ubiquitous, on-demand network access toa shared pool of configurable computing resources that can includenetworks, servers, storage, applications, and services that can berapidly provisioned and released with minimal management effort.

As shown in FIG. 1A, in one embodiment, typical users 100 of thecomputer system 130 can be individuals, institutions and/or otherapplications or systems. Individuals, for example, can includeemployees, spouses of employees, human resources staff at employers,staff at retirement plan administrators, financial advisors,accountants, tax professionals etc. Institutions can include employers,plan administrators, financial services firms, tax advisory firms andsuch. The users of the computer system can also be other applications orthird-party systems such as retirement planning systems/wealthmanagement systems/portfolio management systems/online accountinformation websites of employers and/or retirement planadministrators/mobile applications offered by the institutions indicatedabove. The users can also be computer batch programs or scripts.

Users can interact with the computer system via a graphical userinterface (GUI) such as a web browser, or via the interfaces of devicessuch as tablets, mobile phones, smartphones and other electronicdevices. The users may also interact with the system via APIs(application programming interfaces), computer batch interfaces and/orscripting tools.

As shown in FIG. 1A, input data (employee and employer information) 120from a user 100 is sent to the computer system 130 via data network 110.The data network 110 may be any suitable data network for transmittinginformation such as the Internet, an intranet, an extranet, etc. It canalso use other types of communication networks such as the Ethernet andcan also include wired and/or wireless connections.

Furthermore, as shown in FIG. 1B, the remote computing device computer190, in one or more configurations is able to connect directly, orthrough the Internet using appropriate communication protocols, to oneor more account servers or computers 135 to access, change or alter datastored therein. In a further arrangement, the computer system 130 isalso configured to optionally communicate with the account servers andexchange information.

With reference to FIGS. 3A and 3B, in one or more embodiments, thesystem described includes a computer system 130 properly configured bycode executing therein to implement an input retrieval step 300. Thisinput retrieval step is, in one arrangement, implemented by a series ofmodules or sub-modules that configure a processor thereof to access orreceive data from a retirement plan participant. In a particularimplementation not shown, the information accessed or received by thecomputer 130 in step 300 is input into a graphical user interfacedisplayed on a remote or local computer, such as computer 190. Withreference to FIG. 2 , the input data consists, in a non-limitingarrangement, of employee and employer information 200 sent by the user.A general description 210 and an example 220 of the data sent by a userare also provided. For example, the computer system 130 receives inputdata (employee and employer information) from the user. The scores arecalculated using the input data. For example, the input data 200 is usedby the computer system 130 to calculate scores and deviserecommendations, which are then, transmitted 180 to the user via datanetwork 110. Likewise, Annual compensation data is used. This is thetotal eligible compensation for the year. This typically includessalary, bonus, and commissions. Other data sets and values used are:

How often the employee is paid—This is the payment cycle. Typical valuescan include Weekly, Bi-Weekly, Monthly, Bi-Monthly, Annually. Number ofpay checks remaining for the year—The number of pay checks that areremaining for the rest of the year. YTD employee contribution—Theyear-to-date contribution made by the employee. Current employeecontribution rate—The current rate of contribution by the employeetowards the retirement plan. YTD employer matching contribution—Theyear-to-date matching contribution made by the employer. Currentemployer match rate—The current rate of matching contribution providedby employer. Max employer match rate—The maximum rate of matchingcontribution that can be provided by employer. YTD employer non-electivecontribution—The year-to-date non-elective contribution made by theemployer. This typically includes any profit sharing contributions madeby the employer. Employee age>=50 during the year—Will the employee be50 years old or above during the year. Employee federal tax rate—Thefederal tax rate of the employee. Employee state tax rate—The state taxrate of the employee. Score calculation year—The year for which thescores are calculated. Employer Name—The name of the employer. Type ofretirement plan—The type of retirement plan. The most common one is401K. Plan permits catch-up contributions—It indicates whether theretirement plan permits catch-up contributions for employees 50 years orabove.

In some other embodiments, all or a portion of the input data may bederived based on the input data received from the user. For example, theCurrent Employer Match Rate and the Max Employer Match Rate can beobtained by querying the database 170, and as stipulated for the givenCompany Name and Current Employee Contribution Rate shown in FIG. 6 .

It should also be noted that in some embodiments, instead of a usersupplying input data, the system can connect to anotherapplication(s)/system(s) and gather input data.

Returning to FIG. 3A, the computer system 130 is configured, using oneor more modules to perform pre-score calculations as in step 310, so asto calculate the scores and devise recommendations. In one particulararrangement, the pre-score computation step 310 involves one or moremodules that configured the computer system 130 to perform intermediatecomputations using the input data received, in order to calculate thevarious scores. This step also includes comparing some of the inputvalues against the limits specified by the IRS for the given year andretirement plan and making any necessary adjustments for performing thevarious calculations.

As examples, some of the values computed at this step can include:

‘Maximum annual compensation to be used’—This is calculated based on theannual compensation received as input data 120 and checking against theannual compensation limit specified in the database 170, and asstipulated by the IRS for the given retirement plan and year provided inFIG. 4 .

‘Compensation per pay check’—This is calculated based on ‘maximum annualcompensation to be used’ and the input data on ‘how often the employeeis paid’

‘Effective employee elective deferral limit’ and ‘Effective overallcontribution Limit’ are calculated based on the limits specified in thedatabase 170, and as stipulated by the IRS for the given retirementplan, year and age of the employee shown in FIG. 4 .

‘Total amount expected to be contributed from now till the end of year’is based on ‘compensation per pay check’, ‘employee contribution rate’and ‘effective number of pay checks remaining to reach contributionlimit for the year’.

‘Total amount expected to be contributed for the year’ is the sum of‘YTD employee contribution’ and ‘Total amount expected to be contributedfrom now till the end of year’

‘Max theoretical employer matching contribution that can be obtained forthe year’ is the product of the ‘Maximum annual compensation to be used’and ‘Max employer match rate’ and is also checked against any Employermatch limit specified in the database 170, as stipulated for the givencompany and retirement plan shown in FIG. 6 .

‘Total expected employer match from now till the end of year’ is theproduct of ‘Compensation per pay check’, ‘Current employer match rate’and ‘Effective number of pay checks remaining to reach contributionlimit for the year’

‘Total amount expected to be matched for the year’ is the sum of ‘YTDemployer matching contribution’ and ‘Total expected employer match fromnow till the end of year’.

The results of the calculations generated in step 310 are used by aproperly configured computer system 130 to perform Employee ContributionScore (ECS) calculations, as shown is step 320. Here, the processor isconfigured to generate a value or values corresponding to the level ofcontribution made by the employee relative to the maximum contributionallowable under law. ECS is calculated by dividing the ‘total amountexpected to be contributed for the year’ by the ‘effective employeeelective deferral limit’ and then multiplying by 100, as shown by theequation below:ECS=(‘Total amount expected to be contributed for the year’/‘Effectiveemployee elective deferral limit’)*100

Additionally, the processor is configured to generate an Employer MatchScore (EMS), as in step 330. The computer system 130 is configured togenerate one or more values which represents the level of matchingcontribution expected to be received from the employer relative to themaximum matching contribution that can be obtained from the employer andis calculated by dividing the ‘total amount expected to be matched forthe year’ by ‘max theoretical employer matching contribution that can beobtained for the year’ and then multiplying by 100, as shown by theequation below:EMS=(‘Total amount expected to be matched for the year’/‘Max theoreticalemployer matching contribution that can be obtained for the year’)*100.

As shown in FIG. 3A, the processor is configured to implement aComposite Score (CS) generation step 340, by one or more modulesexecuting as code within the processor. Step 340 is, in one arrangementa plurality of values depending on user preference and particularcircumstances. In one embodiment, of the system and methods described,two different types of composite scores that can yield different valuesare generated contemporaneously, or individually. The scores providedenable or address differing approaches to generating necessaryinformation for enabling the optimization of a retirement benefit. Forexample, the computer system 130 is configured to generate one or moreof:

i) Composite Score Type 1 (CS_1) represents an overall score that treatscontribution made by the employee and the matching contribution providedthe employer equally without any differentiation. CS_1 is calculated bytaking the arithmetic mean of the Employee Contribution Score (ECS) andEmployer Match Score (EMS).CS_1=(ECS+EMS)/2

ii) Composite Score Type 2 (CS_2) represents the overall level of thetotal contribution made by the employee and the matching contributionreceived from the employer. CS_2 is calculated by taking a weightedaverage of the Employee Contribution Score (ECS) and the Employer MatchScore (EMS). The weights are based on the ‘Effective Employee ElectiveDeferral Limit’ and the ‘Max Theoretical Employer Matching Contributionthat can be obtained for the year’ and are calculated as follows:Employee Contribution Score Weight (ECS_W2)=Effective employee electivedeferral limit/(Effective employee elective deferral limit+Maxtheoretical employer matching contribution that can be obtained for theYear.Employer Match Score Weight (EMS_W2)=Max theoretical employer matchingcontribution that can be obtained for the year/(Effective employeeelective deferral limit+Max theoretical employer matching contributionthat can be obtained for the year).CS_2=(ECS_W2*ECS)+(EMS_W2*EMS).

Thus CS_2 represents an overall score that indicates how effectively anemployee is maximizing the total contribution benefit provided by theretirement plan in terms of taking advantage of the maximum amount thatcan be contributed for the year as well as availing the maximum matchingcontribution from the employer.

It should be noted that in this score, a $1 contribution made by theemployee is valued the same/valued at the same level as the $1 inmatching contribution received from the employer.

In the current embodiment of the invention, the scores range from 0-100.But the scores can be represented in many different numeric ranges ormany different modes of ranges namely as letter grades such as A+, A,A−, B+, B, B− etc., descriptions such as High/Medium/Low etc.,descriptions such as Excellent/Good/Poor etc., descriptions or colorssuch as Red/Amber/Green etc. The mapping indicated in FIG. 5 may be usedfor this purpose.

Once the scores are calculated, the one or more processors of the systemdescribed is configured by code executing therein to derive or deviserecommendations for optimization of the participants retirement benefitsas in step 350. In one embodiment, a suitably configured processorgenerates one or more recommendations, which can comprise one or moresuggested changes to the user input data, for improving scores andmaximizing benefits. For example, the computer system 130 is configuredto calculate, through one or more modules, the additional amount theemployee may contribute to maximize tax savings. Likewise, the amount ofadditional tax saving available to the participant, based in oneimplementation, on the employee's federal and state tax rates, is alsocalculated. In a further, non-limiting arrangement, the processor isconfigured to calculate any free money that is left in terms of lostmatching contribution from the employer. In yet another embodiment, thesystem is configured by code executing in a processor thereof, toprovide specific recommendation on actions or changes in user data thatwill result in a maximization or optimization of employee tax savings.Additionally, the maximization can take into account how to obtain themaximum matching contribution from the employer.

In one or more embodiments, the system is configured to evaluate thescores generated, using one or more machine learning algorithms orapplications, such as deep learning appliances, neural networks, supportvector machines, genetic algorithms, linear regression and otherapproaches to feature selection, feature detection, correlative datasets, or data mining. For example, the computer system 130 is configuredto evaluate the scores, input data, historical data, or otherinformation available from local and remote sources, including accessedvia the Internet, to generate a ranking or hierarchy of scores and theprobability that each score or generated recommendation will achieve anaim or goal of the participant.

With further reference to FIG. 3B, as shown in step 360 the computersystem 130 is configured to send the scores and recommendations(including values corresponding to the additional amount that can becontributed to maximize tax savings, amount of additional tax that canbe saved, free employer match left on the table and specificrecommendation for maximizing tax savings and getting the maximummatching contribution from the employer) to the remote computer 190.

With reference to FIG. 3B, upon receiving the calculated scores andrecommendations generated during step 360, one or more processors of theremote computer 190 is configured to generate a graphical representationthat visually depicts (i) each of the contribution strategies, (ii) agraphical indicator identifying the rank or generate a hierarchy of eachstrategy relative to one another, where each depicted contributionstrategy, as shown in step 370.

The processor of the remote device 190 is further configured toassociate a resource link or data object with each contributionstrategy, whereby the selection of the link or data object by theparticipant causes the remote device 190 to send one or moreinstructions to the computing device to implement the selectedcontribution strategy as shown in step 380 of FIG. 3B.

In one instance, the link is a formatted URL string. In anothernon-limiting example, the data object is JSON file that contains querydata. Upon selection of the graphical representation, such as byclicking or tapping on the proposed recommendation, the URL, JSON fileor data object is sent to a remote account server 135, or the computersystem 130 for further processing or parsing.

With further reference and provided in step 390, the link or data objectis transmitted back to the computer system 130, account server 135 orsystem where the object or link is parsed, inspected or implemented. Inone arrangement, the data object contains the desired values for one ormore participant data fields stored in a participant account server, andan authorization from the participant to make such changes.

Upon receiving such a data object or link, the relevant computing systemeffectuates the changes, and alters one or more factors related to theparticipant's retirement account or approach.

In one or more further implementations, the system described can connectto a third-party system/external system such as a retirement planadministrator system/human resources system/portfolio management system,without any manual intervention, and automatically change the employeecontribution rate so that the employee contributes to the maximumallowable under law and maximize his/her tax benefits.

Furthermore, the system is configured by code executing in at least oneprocessor thereof, the above-mentioned automated process every yearwithout any manual intervention. This will be of invaluable benefit tothe employees since they do not have to keep track of changingcircumstances such as changes in compensation, change of employer,changes in employer match rules, changes in IRS contribution limits etc.and ensure that they maximize their employer match and/or contribute tothe maximum allowable under law for any given year.

In a specific implementation of the system describes, the retirementoptimization computer system 130 connects to third-party via securecommunication protocols. Such communications protocols can include, butnot limited to, methods/protocols such as http, https, sftp, messagequeues, remote method invocation, application programming interfacesetc. Furthermore, such communications between the computer system 130,the remote device 190 and one or more remote services (135) is encryptedprior to transmission.

Once the system makes the automated changes, the system can sendnotification messages to the user which can include, but not limited to,email messages/mobile phone text messages/printed confirmationstatements etc.

While there exist multiple ways of implementing the steps and systemsprovided, several scenarios are shown in the table given below by way ofnon-limiting examples:

EXAMPLES

Input Data Example 1 Example 2 Example 3 Example 4 Annual $100,000$100,000 $100,000 $100,000 Compensation How Often The Bi-WeeklyBi-Weekly Bi-Weekly Bi-Weekly Employee Is Paid Number Of Pay 26  26  26 26 Checks Remaining  For The Year YTD Employee $0 $0 $0 $0 ContributionCurrent Employee  3% 36%  9% 18% Contribution Rate YTD Employer $0 $0 $0$0 Matching Contribution Current Employer  3%  6%  6%  6% Match Rate MaxEmployer  6%  6%  6%  6% Match Rate YTD Employer $0 $0 $0 $0 NonelectiveContribution Employee Age >= No No No No 50 During the Year Employee 25%25% 25% 25% Federal Tax Rate Employee State  7%  7%  7%  7% Tax RateScore Calculation 2015 2015 2015 2015 Year Employer Name Company ACompany A Company A Company A Type of Traditional TraditionalTraditional Traditional Retirement Plan 401 (k) 401 (k) 401 (k) 401 (k)Plan Permits Yes Yes Yes Yes Catch-up Contributions Pre-ScoreComputations All items below are calculated values Maximum Annual$100,000 $100,000 $100,000 $100,000 Compensation To Be Used Compensation$3,846 $3,846 $3,846 $3,846 Per Pay Check Employee $18,000 $18,000$18,000 $18,000 Elective Deferral Limit Catchup $0 $0 $0 $0 ContributionLimit Denominator for Effective $18,000 $18,000 $18,000 $18,000Calculating ECS Employee Elective Deferral Limit Theoretical $53,000$53,000 $53,000 $53,000 Overall Contribution Limit Effective Overall$53,000 $53,000 $53,000 $53,000 Contribution Limit Total YTD $0 $0 $0 $0Employee and Employer Contributions Current Employee $115.38 $1,384.62$346.15 $692.31 Contribution Per Pay Check Current Employer $115.38$230.77 $230.77 $230.77 Match Per Pay Check Total Amount $3,000 $18,000$9,000 $18,000 Expected To be Contributed From Now Till End of YearNumerator for Total Amount $3,000 $18,000 $9,000 $18,000 Calculating ECSExpected To Be Contributed For The Year Denominator for Max Theoretical$6,000 $6,000 $6,000 $6,000 Calculating EMS Employer MatchingContribution That Can Be Obtained For The Year Total Expected $3,000$3,000 $6,000 $6,000 Employer Match From Now Till End Of Year Numeratorfor Total Amount $3,000 $3,000 $6,000 $6,000 Calculating EMS Expected ToBe Matched For The Year Calculate ECS Employee 17 100  50 100Contribution Score (ECS) Calculate EMS Employer Match 50  50 100 100Score (EMS) Calculate Composite Scores CS_1 Employee  0.5  0.5  0.5  0.5Contribution Score Weight Employer Match  0.5  0.5  0.5  0.5 ScoreWeight Composite 33  75  75 100 Score Type 1 (CS_1) CS_2 Employee  0.75 0.75  0.75  0.75 Contribution Score Weight Employer Match  0.25  0.25 0.25  0.25 Score Weight Composite 25  88  63 100 Score Type 2 (CS_2)Devise Recommendations Additional $15,000 $0 $9,000 $0 Amount That CanBe Contributed To Maximize Tax Savings Amount of $4,800 $0 $2,880 $0Additional Tax That Can Be Saved Free Employer $3,000 $3,000 $0 $0 MatchLeft On The Table Recommendation Increase Decrease No Change No ForGetting The Current Current Required Change Maximum Employee EmployeeRequired Matching Contribution Contribution Contribution From Rate fromRate from The Employer 3% to 6% 36% to 6% Recommendation IncreaseDecrease Increase No For Maximizing Current Current Current Change TaxSavings Employee Employee Employee Required Contribution ContributionContribution Rate from Rate from Rate from 3% to 18% 36% to 18% 9% to18% Recommendation Increase Decrease Increase No For Getting The CurrentCurrent Current Change Maximum Employee Employee Employee RequiredMatching Contribution Contribution Contribution Contribution From Ratefrom Rate from Rate from The Employer As 3% to 18% 36% to 18% 9% to 18%Well As Maximizing Tax Savings

The invention thus not only provides scores that are descriptive of thecurrent situation of an employee but also delivers additional value byproviding specific recommendations on how the employee can improvehis/her retirement benefits.

It should also be noted that the system can be used to generate scoresfor any year for which input data is available. For example, the systemcan be used to generate scores for past years giving an employee thecapability to understand how he/she performed historically. These scoresmay be plotted on a graph or represented as a chart. Additionally, theusers of the system can generate scores for one or more employees forone or more years for one or more companies to do analyses and studiesthat can include but not limited to how an employee or employeesperformed year-over-year in terms of their own contribution, matchingcontribution from the employer, any free money they left on the table.This can be useful in devising policies to help employees save more andhave a secure retirement life.

It may be noted that in some embodiments, the system may be deployed ona cloud environment, which a user can access via a data network, passinput data, and get scores and recommendations from the system.

In other embodiments, a user can download, deploy and run the wholesystem as an application on a mobile device such as a cell phone,smartphone, tablet device or other such handheld devices or on acomputer device such as a laptop, desktop, server etc.

In some other embodiments, another application such as a third-partyapplication can access the system, pass input data, and get scores andrecommendations from the system, which the third-party application maythen use for its own purposes such as displaying to its users.

In yet another embodiment, a computer batch program requiring scores andrecommendations for one or more employees, may access the system, passinput data pertaining to one or more employees, and get scores andrecommendations from the system for the said one or more employees.

The scores and recommendations created by the system may be displayed onthe screens of one or more electronic devices and/or printed on paper.The scores and recommendations may also be stored as electronic files,transferred or shared between computers, or projected onto a screenduring presentations.

It should be understood that the manner in which the system is deployed,accessed, and/or how the scores and recommendations generated by thesystem are displayed or used, are in no way a limitation on the utility,novelty, or inventiveness of the system.

The computer system described herein can be developed to run on a widevariety of operating systems including but not limited to variousversions of Apple iOS, Apple OS X, Android, Windows, UNIX, Linux andother operating systems. The capability of the system is in no waydependent upon or limited by the underlying operating system used.

The computer methods used for calculating the scores and devising therecommendations can be developed by a computer programmer/developerskilled in the art. The computer methods may be implemented in a varietyof programming languages including but not limited to Swift,Objective-C, Java, C#, .NET, C++, Perl, Python and other programminglanguages. The capability of the system is in no way dependent upon orlimited by the underlying programming language used.

Some of the figures included herein depict flow charts/diagrams that mayshow a particular logic flow indicating the execution of a particularlogic. It must be noted that the particular logic flow merely providesan exemplary implementation of the general functionality describedherein. Additionally, the particular logic flow does not necessarilyhave to be executed in the same order indicated unless otherwise stated.Furthermore, the particular logic flow may be implemented by a hardwarecomponent, a software component executed by a computer, a firmwarecomponent embedded in hardware, or any combination thereof.

The computer system described herein may consist of one or moreprocessors, communicating with one or more memory units and one or moredatabases, via one or more data circuits. The data circuits may carryelectrical signals between the processor(s), the memory unit(s) and thedatabase(s).

The executable instructions that cause the computer system to executethe various methods for calculating the scores and devisingrecommendations can be stored and delivered in any type ofcomputer-readable format including but not limited to a hard drive, pendrive, flash drive, optical drive or CD-ROM. The executable instructionsmay also be downloaded from a remote location to a user's computer via awired or wireless network. This does not imply that the executableinstructions take the form of a signal or other intangible form.

It should be understood that various combination, alternatives andmodifications of the present invention could be devised by those skilledin the art. The present invention is intended to embrace all suchalternatives, modifications and variances that fall within the scope ofthe appended claims.

While the invention has been particularly shown and described withreference to a preferred embodiment thereof, it will be understood bythose skilled in the art that various changes in form and details may bemade therein without departing from the spirit and scope of theinvention.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

It should be noted that use of ordinal terms such as “first,” “second,”“third,” etc., in the claims to modify a claim element does not byitself connote any priority, precedence, or order of one claim elementover another or the temporal order in which acts of a method areperformed, but are used merely as labels to distinguish one claimelement having a certain name from another element having the same name(but for use of the ordinal term) to distinguish the claim elements.

Also, the phraseology and terminology used herein is for the purpose ofdescription and should not be regarded as limiting. The use of“including,” “comprising,” or “having,” “containing,” “involving,” andvariations thereof herein, is meant to encompass the items listedthereafter and equivalents thereof as well as additional items.

Particular embodiments of the subject matter of the present inventionhave been described. Other embodiments are within the scope of thefollowing claims. For example, the actions recited in the claims can beperformed in a different order and still achieve desirable results. Asone example, the processes depicted in the accompanying figures do notnecessarily require the particular order shown, or sequential order, toachieve desirable results. In certain embodiments, multitasking andparallel processing can be advantageous.

Unless the context clearly requires otherwise, throughout thedescription, the words “comprise,” “comprising,” and the like are to beconstrued in an inclusive sense as opposed to an exclusive or exhaustivesense; that is to say, in a sense of “including, but not limited to.”Words using the singular or plural number also include the plural orsingular number respectively. Additionally, the words “herein,”“hereunder,” “above,” “below,” and words of similar import refer to thisapplication as a whole and not to any particular portions of thisapplication. When the word “or” is used in reference to a list of two ormore items, that word covers all of the following interpretations of theword: any of the items in the list, all of the items in the list and anycombination of the items in the list.

Publications and references to known registered marks representingvarious systems are cited throughout this application, the disclosuresof which are incorporated herein by reference. Citation of the abovepublications or documents is not intended as an admission that any ofthe foregoing is pertinent prior art, nor does it constitute anyadmission as to the contents or date of these publications or documents.All references cited herein are incorporated by reference to the sameextent as if each individual publication and references werespecifically and individually indicated to be incorporated by reference.

The above descriptions of embodiments of the present invention are notintended to be exhaustive or to limit the systems and methods describedto the precise form disclosed. While specific embodiments of, andexamples for, the apparatus are described herein for illustrativepurposes, various equivalent modifications are possible within the scopeof other articles and methods, as those skilled in the relevant art willrecognize. The teachings of articles and methods provided herein can beapplied to other devices and arrangements, not only for the apparatusand methods described above.

The elements and acts of the various embodiments described above can becombined to provide further embodiments. These and other changes can bemade to the apparatus and methods in light of the above detaileddescription.

What is claimed is:
 1. A system for calculating employee retirementoptimization comprising: an optimization computer having one or moreprocessors configured by code executing therein to access accountcontribution data relating to an account held by a participant in aretirement plan wherein the accessed data is less than one year old, andderive, based on the accessed data, one or more values indicative of thecurrent status of one or more features of the account, and a hierarchyof proposals to maximize one of the one or more features of theretirement account for the current calendar year, wherein deriving thehierarchy of proposals includes accessing one or more valuescorresponding to current contributions made within the current year tothe account by the participant and one or more values corresponding to amaximum possible contribution made to the account by the participant forthe current year and to transmit such a derived hierarchy and the one ormore values indicative of the current status of one or more features ofthe account; the optimization computer further configured to rank thehierarchy of proposals using a machine learning model trained on ahistorical data set for one or more participants, wherein the hierarchyof proposals are provided as an input to the machine learning model anda probability is generated for each of the hierarchy of proposals thatcorresponds to the likelihood that each of the hierarchy of proposalswill meet the contribution goal of the participant; a remote deviceconfigured to receive the one or more values indicative of the currentstatus values and the hierarchy of retirement proposals and generate inresponse to the transmission, (i) a plurality of graphical elements foreach of the received one or more values indicative of the current statusvalues wherein each of the received one or more values indicative of thecurrent status values is assigned a non-numerical graphical elementcorresponding to a pre-determined range of values for the one or morevalues indicative of the current status values, and (ii) a graphicalrepresentation of each particular retirement proposal of the hierarchyof retirement proposals, whereby upon selection by a user of aparticular graphical representation of a particular retirement proposalon the remote device, the remote device is configured to send aninstruction to the optimization computer to generate a Javascript ObjectNotation (JSON) data object including at least an instruction set forinstructing a processor and values correlated to changes in one or moreparameters of the account and send the generated Javascript ObjectNotation (JSON) data object via a communication channel to a retirementaccount computing device; and a retirement account computing deviceremote from the optimization computer and configured by one or moreprocessors executing therein to receive the generated JSON data objectand implement the instructions thereof to parse the values to implementa change in one or more data values corresponding to the currentretirement account of the participant that initiated the instructiontransmission and generate a notification message for transmission to theremote device indicating the change made to the one or more data values.2. The system of claim 1, wherein the retirement optimization computeris configured to access a remote third-party computer system.
 3. Thesystem of claim 2, wherein the remote third party system is one of aretirement plan administrator system, a human resources system, aportfolio management system, or a social network, or a messaging system.4. The system of claim 2, is further configured to access, from thethird-party-system, a historical dataset covering at least one prioryear for the participant, the historical dataset including a valuecorresponding to a prior contribution limit for the participant a givenprior year, the prior contribution amount made by the participant in thegiven prior year, a matching limit for the participant that specifiesthe amount that the participant's employer would match a contribution tothe retirement account of the participant for the prior given year, andthe amount actually matched by the employer in the prior given year, andgenerate, one or more non-numerical indicators corresponding to thedifference between the historical dataset for the participant and thecurrent participant data.
 5. A computerized method for maximizingcontributions to employee retirement plans, comprising: receiving, by aprocessor of a computing device, an input data set for a given employeethat includes at least: (i) participant data, (ii) a contribution limitfor the participant that specifies a total amount the participant maycontribute to a tax-savings retirement account, (iii) a currentcontribution amount that specifies the total amount that the participanthas contributed to a retirement account for the current year, (iv) amatching limit for the participant that specifies the amount that theparticipant's employer will match a contribution to the retirementaccount of the participant for the current year, and (v) a currentmatching amount that specifies the matching amount that the employer hasalready contributed to the retirement account of the participant for thecurrent year; generating, by a processor of the computing device, atleast: (i) one employer contribution maximization value indicating thedifferential between the maximum employee matching funds and the amountof funds presently contributed to the retirement account by theemployer; and (ii) at least one tax savings maximization value beingderived from at least a comparison of a total amount permitted in a taxsavings retirement account and the current amount contributed to theretirement account by the employee; devising, by a processor of thecomputing device, a plurality of contribution strategies that include atleast one contribution strategy to (i) minimize the employercontribution maximization value, at least one contribution strategy to(ii) minimize the tax savings maximization value, and at least onecontribution strategy to (iii) achieve the smallest possible value ofboth (i) and (ii), wherein the computing device is further configured torank the devised strategies based on (a) the participant data and (b) alikelihood that the each of the devised strategies will meet thecontribution goal of the participant, the likelihood determined byproviding a historical data set for the participant to one or moremachine learning applications configured to generate a likelihood ofsuccess value based on a correlation between the devised strategy andthe historical data; transmitting, by the computing device, theplurality of contribution strategies, the employer contributionmaximization value and tax saving maximization value to a remotecomputing device over the Internet using a communication channel,generating, by the remote computing device on a display connectedthereto, a graphical representation that visually depicts (i) the taxsaving maximization value and the employer contribution maximizationvalue, each as one of a plurality of non-numerical visual indicators,wherein each non-numerical visual indicator corresponds to apre-determined range of values, and (ii) each of the plurality ofcontribution strategies, wherein each of the visually depicted pluralityof contribution strategies is provided with a graphical indicatoridentifying the relative amount of improvement each strategy will impartto the tax savings maximization value and the contribution maximizationvalue if implemented; associating, with the remote computing device, aresource link associated with each depicted contribution strategy,wherein selection of the link causes a processor of the computing deviceto generate at least one file, the file including at least aninstruction set for instructing a processor and one or more valuescorrelated to changes in one or more parameters of the account and sendthe at least one data object to a retirement account computing deviceconfigured by one or more processors to implement the selectedcontribution strategy according to the instructions provided in the atleast one file.
 6. The method of claim 5, further comprising: receiving,by an account management computing device, at least one file from aprocessor of the computing device and an authorization from theparticipant to implement the change in the retirement plan; andaccessing, by the account management computing device, one or moreaccounts on an account server over the Internet, belonging to theparticipant and for which user authorization has been provided andimplementing the instructions contained within the at least one file foraltering one or more values associated with the account of theparticipant.
 7. The method of claim 5, wherein the employer contributionmaximization value is derived using at least the current participantcontribution amount and the current participant contribution rate. 8.The method of claim 6 wherein the accessing step further comprisesaccessing the server through a security layer.
 9. The method of claim 5further comprising, generating a combined score value according to:CS=(ECSW2*ECS)+(EMSW2*EMS), where ECSW2 is a value representing theeffective employee elective deferral limit/(effective employee electivedeferral limit+maximum theoretical employer matching contribution thatcan be obtained for the year) and EMSW2 is a value representing amaximum theoretical employer matching contribution that can be obtainedfor the year/(effective employee elective deferral limit+maximumtheoretical employer matching contribution that can be obtained for theyear), EMS corresponds to the employer contribution maximization valueand ECS corresponds to the tax savings maximization value, andtransmitting the combined score value along with the employercontribution maximization value and tax savings maximization value. 10.The computerized method of claim 5, wherein the participant dataincludes at least one of: the total eligible compensation for the yearincluding salary, bonus, and commissions; payment cycle selected from agroup including Weekly, Bi-Weekly, Monthly, Bi-Monthly, and Annually;number of pay checks that are remaining for the rest of the year;year-to-date contribution made by the employee; current rate ofcontribution by the employee towards the retirement plan; year-to-datematching contribution made by the employer; current rate of matchingcontribution provided by the employer; maximum rate of matchingcontribution that can be provided by the employer; year-to-datenon-elective contribution made by the employer including any profitsharing contributions made by the employer; Employee age>=50 during theyear; federal tax rate of the employee; state tax rate of the employee;year for which the scores are calculated; name of the employer; type ofretirement plan opted—the most common one is 401K; and whether planpermits catch-up contributions for employees 50 years or above accordingto specific retirement plan.
 11. The method of claim 5, whereingenerating at least one tax savings value includes calculating anEmployee Contribution Score (ECS) representative of the level ofcontribution made by the participant relative to the maximumcontribution allowable under an applicable regulation.
 12. The method ofclaim 11, wherein the ECS is calculated as (‘Total amount expected to becontributed for the year’/‘Effective employee elective deferrallimit’)*100.
 13. The method of claim 5 wherein generating thecontribution values includes calculating an Employer Match Score (EMS)representing the level of matching contribution expected to be receivedfrom the employer of a participant relative to the maximum matchingcontribution that can be obtained from the employer.
 14. The method ofclaim 13, wherein the EMS is calculated as EMS=(‘Total amount expectedto be matched for the year’/‘Max theoretical employer matchingcontribution that can be obtained for the year’)*100.
 15. The method ofclaim 5, further comprising calculating a combined score (CS) derivedfrom at least an Employee Contribution Score (ECS) representative of thelevel of contribution made by the participant relative to the maximumcontribution allowable under an applicable regulation and an EmployerMatch Score (EMS) representing the level of matching contributionexpected to be received from the employer of a participant relative tothe maximum matching contribution that can be obtained from theemployer.
 16. The computerized method of claim 5 wherein thecontribution strategy devised includes altering the amount the employeemay contribute to maximize employer match and/or tax savings,calculating the amount of additional tax that can be saved based on theemployee's federal and state tax rates and the amount of money that isleft in terms of lost matching contribution from the employer.
 17. Themethod of claim 5, further comprising: generating, by the computingdevice, a recalculated contribution strategy score for the user uponimplementation of the selected contribution strategy; transmitting, bythe computing device, the recalculated contribution strategy score tothe remote computing device; and displaying, by the remote computingdevice, the recalculated contribution strategy score as a graphicalrepresentation that visually depicts the recalculated contributionstrategy score as at least one of non-numerical visual indicators,wherein each non-numerical visual indicator corresponds to apre-determined range of values.